Identifying software responsible for changes in system stability

ABSTRACT

A computer-implemented method detects a stability change in a computer system, and identifies a first set of at least one capability of the computer system that is affected by the stability change. In response to detecting the stability change, the method identifies a software application that was installed prior to the stability change, and identifies a second set of at least one capability of the computer system that is utilized by the identified software application. The method compares the first and second capability sets to determine a degree of similarity, and compares the time that the stability change was detected to the time that the identified software application was installed to determine a temporal proximity. The method then identifies the likelihood that the identified software application is the cause of the stability change, wherein the identified likelihood is a function of the degree of similarity and the temporal proximity.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of co-pending U.S. patent applicationSer. No. 13/690,900, filed on Nov. 30, 2012.

BACKGROUND

1. Field of the Invention

The present invention relates to monitoring and managing the operationalstability of a computer system.

2. Background of the Related Art

Physical computer systems and virtual machines rely upon various typesand versions of software applications in order to complete their tasks.These software applications may include operating systems, drivers,firmware, and user applications. New and different software applicationsmay be installed into one of these systems or machines from time to timeto alter, maintain or update the software capabilities. Ongoinginstallation of software makes this a potentially dynamic environment.In fact, software package update managers may be utilized to performroutine software updates.

However, the installation of a software application, including asoftware update, may lead to a system event that impacts the performanceof the system. These system events may be referred to as faults,instabilities, or errors. When a systems management tool detects such afailure or instability in a computer system, the systems management toolis capable of triggering the collection and storage of a log.Administrative personnel may then access the log in order to determinethe cause of the problem and attempt to fix the problem.

BRIEF SUMMARY

One embodiment of the present invention provides a computer-implementedmethod, comprising detecting a stability change in a computer system,and identifying a first set of at least one capability of the computersystem that is affected by the stability change. The method furthercomprises, in response to detecting the stability change, identifying asoftware application that was installed or updated to the computersystem prior to the stability change, and identifying a second set of atleast one capability of the computer system that is utilized by theidentified software application. The method compares the first set of atleast one capability to the second set of at least one capability todetermine a degree of similarity, and compares a first time that thestability change was detected to a second time that the identifiedsoftware application was installed or updated to determine a temporalproximity. The method then identifies the likelihood that the identifiedsoftware application is the cause of the stability change, wherein theidentified likelihood is a function of the degree of similarity and thetemporal proximity.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

FIG. 1 is a schematic diagram of a management node capable of monitoringthe stability of multiple servers.

FIG. 2 is a flowchart of a method of identifying software applicationsthat are responsible for system stability changes in one or more of theservers.

FIG. 3 is a diagram of a cloud computing node according to one or moreembodiment of the present invention.

FIG. 4 is a diagram of a cloud computing environment according to one ormore embodiment of the present invention.

FIG. 5 is a diagram depicting abstraction model layers according to oneor more embodiment of the present invention.

FIG. 6 is a diagram of an exemplary computing node that may be utilizedaccording to one or more embodiments of the present invention.

FIG. 7 is a diagram of an exemplary blade chassis that may be utilizedaccording to one or more embodiments of the present invention.

DETAILED DESCRIPTION

One embodiment of the present invention provides a computer-implementedmethod, comprising detecting a stability change in a computer system,and identifying a first set of at least one capability of the computersystem that is affected by the stability change. The method furthercomprises, in response to detecting the stability change, identifying asoftware application that was installed or updated to the computersystem prior to the stability change, and identifying a second set of atleast one capability of the computer system that is utilized by theidentified software application. The method compares the first set of atleast one capability to the second set of at least one capability todetermine a degree of similarity, and compares a first time that thestability change was detected to a second time that the identifiedsoftware application was installed or updated to determine a temporalproximity. The method then identifies the likelihood that the identifiedsoftware application is the cause of the stability change, wherein theidentified likelihood is a function of the degree of similarity and thetemporal proximity.

The method may detect a stability change that is either an increase inan amount of stability or an increase in an amount of instability.Existing system management tools are capable of identifying thecondition associated with a stability change. Accordingly, a stabilitychange is typically detected by a management node, such as a VM machinemanager. Preferably, the method will detect stability changes of bothtypes and identifies software applications that are likely to havecaused either stability or instability. A stability change in a computersystem may manifest itself as CPU utilization that is greater than apredetermined CPU utilization threshold, network utilization that isless than a predetermined network utilization threshold, or memoryutilization that is less than a predetermined memory utilizationthreshold. Accordingly, when a stability change is detected, the methodmay identify a first set of at least one capability of the computersystem that is affected by the stability change. For example, the firstset of at least one capability may include one or more capabilityindependently selected from CPU utilization, memory utilization, andnetwork connectivity. A common example of system instability is when aparticular software application goes into a “not responding” state. Thatparticular software application is linked to the system freezing and thesystem's stability change.

The stability change may be correlated to an operating system (OS)event, such as, without limitation, installation of new software,installation of a software update, uninstallation of software, andperformance of maintenance operations. A software application that wasinstalled or updated to the computer system prior to the stabilitychange may be identified by reading a log of OS events. A managementmodule or node will typically maintain a log of OS events. A managementmodule may, for example, reside on an individual computer, whereas amanagement node may, for example, reside in a computer system having aplurality of servers in communication with the management node.

The software application that is identified may be an update to a driveror firmware, an updated version of a previously installed softwareapplication. Drivers allow an operating system to interface with variousdevices of a computer system. A fault or failure of a driver is a likelysource of a stability change. Accordingly, the identified softwareapplication may include a driver for a hard disk drive, a networkinterface, or an input/output port. The software application may also bepart of a virtual machine or running within a virtual machine.

A second set of at least one capability of the computer system that isutilized by the identified software application (i.e., a “scope ofimpact”) may be identified by obtaining the advertised capabilities ofthe software, such as in a manner similar to how Common InformationModel (CIM) Providers let the CIMOM know what services they provide.Software could be required to broadcast its capabilities or useleveraging art to determine capabilities of software based on that.Alternatively, a system administrator could manually input thecapabilities that should be associated with each software applicationaccording to its type. For example, a database application would use thecapabilities of the processor and memory, a web browser applicationwould make heavy use of network capabilities, a hard disk driver wouldbe associated only with storage, and the like. Such a manual input couldbe done ahead of time and stored so that this information was availableeach time a software application of that type is being analyzed todetermine its likelihood of responsibility for a stability change. Asone non-limiting example, the installation of a network driver (the “OSevent”) might cause irregularity in network traffic (the “scope ofimpact”), but not cause a problem with a video card (which is outsidethe “scope of impact”).

A degree of similarity may be determined by comparing the first set ofat least one capability to the second set of at least one capability.For example, there is a high degree of similarity when the capabilitiesutilized by a given software application are exactly the same as thecapabilities that are experiencing a stability change. In a specificexample, a driver to a network interface card interacts mostly with thenetwork interface card. If there is a sudden increase of instabilityexperienced by the network card, yet the processor and memory of thesame computer system are unaffected, then there is a high degree ofsimilarity between the first set of capabilities (those affected by thestability change) and the second set of capabilities (those related tothe nature of the software).

In one embodiment, the degree of similarity may be a numerical value,such as a percentage. For example, the degree of similarity may be equalto the number of capabilities of the software in common with thecapabilities affected by the stability change minus the number ofcapabilities of the software that are not affected by the stabilitychange, divided by the number of capabilities affected by the stabilitychange. Accordingly, the degree of similarity would be a fraction orpercentage not exceeding a value of one. Software having the same exactcapabilities as those capabilities affected by a stability change wouldhave a degree of similarity of 100% (value of one), whereas softwarehaving no capabilities in common with the stability change would have adegree of similarity of 0% (value of zero).

A temporal proximity may be determined by comparing a first time thatthe stability change was detected to a second time that the identifiedsoftware application was installed. A stability change can only beattributed to software that was installed and run prior to the stabilitychange, and it is presumed that faulty software would tend to cause astability change soon after its installation. Accordingly, software thathas been running on the computer system for a long time is probably notthe cause of recent stability change. Rather, a close temporal proximityof the software installation prior to the detection of the stabilitychange is treated by the present methods as increasing the likelihoodthat the given software is responsible for the stability change.

In one embodiment, temporal proximity may be a numerical value, such asa percentage. For example, temporal proximity may be determined only forsoftware installed in the 100 minutes prior to the stability change,where temporal proximity is equal to 100 minus the time in minutes priorto the stability change that the software was installed, divided by 100.Accordingly, software installed 99 minutes prior to the stability changewould have a temporal proximity of 1% (0.01) and software installed 3minutes prior to the stability change would have a temporal proximity of97% (0.97).

The method identifies the likelihood that the identified softwareapplication is the cause of the stability change, wherein the identifiedlikelihood is a function of the degree of similarity and the temporalproximity. That function may be a product of the two measures, such thata high degree of similarity multiplied by a high temporal proximityresults in a high likelihood of responsibility for a stability change.For example, software A may have a degree of similarity of 80% and atemporal proximity of 75% so its likelihood of responsibility is 60%. Bycontrast, software B may have a degree of similarity of 90% and atemporal proximity of 70% so its likelihood of responsibility is 63%. Analternative function might assign a weighting factor to the degree ofsimilarity and a weighting factor to the temporal proximity. Forexample, the weighting factor for the degree of similar (WF1) may be 2and the weighting factor for the temporal proximity (WF2) may be 1,based upon historical data. Accordingly, if the formula for likelihoodof responsibility is equal to (WF1)(degree of similarity)+(WF2)(temporalproximity), the software A has a likelihood of responsibility equal to235% (2*80%+1*75%) and software B has a likelihood of responsibilityequal to 250% (2*90%+1*70%). Other functions may be considered andimplemented without limitation.

Having identified a software application that is likely to beresponsible for the stability change, the method may further compriseremoving the identified software application, presumably if theidentified software application was responsible for an increase ininstability. Similarly, the method may further comprise installing anupdated version of the identified software application, presumably tofix the instability problem. In various embodiments, the updated versionwould only be installed if the updated version has been shown toincrease stability in one or more other computers.

In a further embodiment, the method may include preparing a list ofsoftware applications including the name of the identified softwareapplication and the likelihood that the identified software applicationis the cause of the stability change. Continuing with the previousexample, software A and software B would be listed along with theirlikelihood of responsibility. The likelihood of responsibility for eachsoftware application will depend upon the exact function used, but thefunction should include both the degree of similarity and the temporalproximity.

In yet another embodiment, the list of software applications includessoftware applications likely to increase stability and softwareapplications likely to increase instability. Accordingly, each record inthe list of software application should include a further indicationwhether the stability change, for which the likelihood of responsibilitywas determined, was an increase in stability or an increase ininstability. Over time and across the occurrence of multiple stabilitychanges, the software list may be updated to include softwareapplications that are most likely to increase stability and softwareapplications that are most likely to increase instability.

Although the methods of the invention may be implemented on astand-alone computer system, other embodiments of the method may includeinforming other computer systems that the identified softwareapplication may cause a stability change. Optionally, this may includeinforming at least one other computer system of the likelihood that theidentified software application is the cause of the stability change.This might be done by sending a copy of the foregoing list of softwareapplications that are likely to be responsible for a stability change.In a further option, the list may be broadcast to any computer systemthat is monitoring for such a list.

In a further embodiment, the method prepares a list of softwareapplications having greater than a predetermined likelihood as being thecause of instability in the computer system, and providing the list toat least one other computer system. The other computer system may, inresponse to receiving the list, avoid installing any of the softwareapplications on the list.

In a still further embodiment, the method prepares a list of softwareapplications having greater than a predetermined likelihood as being thecause of stability in the computer system, and providing the list to atleast one other computer system. The other computer system may, inresponse to receiving the list, install one or more of the softwareapplications on the list. This may be the case where the softwareapplication is an update of a software application already installed onthe other computer system.

Still further embodiments of the invention include the sharing ofinformation across multiple networks. Certain forms of informationsharing may be considered crowd sourcing. Various entities orindividuals may agree to share system health data so that the presentmethods have a larger amount of data from which to better identifysoftware applications that are responsible for a system stabilitychange. Alternatively, various entities or individuals may separatelyidentify software applications that are responsible for a systemstability change, but then may agree to share or publish their “problemlist” or “solution list” of software applications.

Embodiments of the invention may be used to analyze system stabilitychanges that occur in various types of systems, such as compute nodes,servers and virtual machines. Across a computer system that managesthousands of VMs, the potential for detecting stability changes andcorrelating those stability changes to a particular software or softwareupdate grows exponentially.

It should be recognized that the methods of the present invention may beperformed as a single task, a periodical task according to a schedule,or a continuous task monitoring systems for stability changes andrecommending potential fixes. Regardless of when the method isperformed, it is not limited to use during a period of softwareinstallation. This is a beneficial aspect of embodiment of theinvention, since installation of a given software application may besuccessfully completed, yet cause the system to experience instabilitywhen the software application is run. For example, a hard disk drive(HDD) driver may not be recognizable as a bad HDD driver until the HDDdriver receives an instruction and causes the system to slow down.

A management node may monitor and store system health metrics over time,including CPU usage, memory usage, and network traffic. When anirregularity is detected, it may be considered an OS event. The methodsof the present invention use this stored list of system informationacross multiple servers or virtual machines in order to pin point thecause of the detected irregularity. Because the stored list of OS eventsis time-stamped, analysis of multiple servers or virtual machines allowsthe method to correlate irregularities (changes in stability) to the useof particular software, such as the progressive installation of asoftware update across the multiple servers or virtual machines in thedata center. A management node using the methods of the presentinvention can distinguish a stability change that is caused by use of aparticular software application from a stability change that is causedby a hardware failure. For example, if a network switch were to fail,all of the systems connected to the network switch will simultaneouslylose connectivity. A bad network software update will manifest itselfonly in those systems that have yet received the bad network softwareupdate.

Another embodiment of the invention provides a computer program productincluding computer usable program code embodied on a tangible computerusable storage medium. The computer program product comprises computerusable program code for detecting a stability change in a computersystem; computer usable program code for identifying a first set of atleast one capability of the computer system that is affected by thestability change; computer usable program code for identifying, inresponse to detecting the stability change, a software application thatwas installed or updated to the computer system prior to the stabilitychange; computer usable program code for identifying a second set of atleast one capability of the computer system that is utilized by theidentified software application; computer usable program code forcomparing the first set of at least one capability to the second set ofat least one capability to determine a degree of similarity; computerusable program code for comparing a first time that the stability changewas detected to a second time that the identified software applicationwas installed or updated to determine a temporal proximity; and computerusable program code for identifying the likelihood that the identifiedsoftware application is the cause of the stability change, wherein theidentified likelihood is a function of the degree of similarity and thetemporal proximity.

The computer program product may further include computer usable programcode for executing, initiating or controlling any of the steps of thecomputer-implemented method described herein.

FIG. 1 is a schematic diagram of a management node 10 capable ofmonitoring the stability of multiple servers 50. The management node 10includes trouble-shooting logic 12, which implements aspects of themethods of the present invention. The trouble-shooting logic 12 hasaccess to a System and OS Events/Faults Log 20, Server Configurationdata 30, and a Problem/Solution Software List 40. The System and OSEvents/Faults Log 20 is a list that is maintained by existing systemmanagement tools. As shown here, the System and OS Events/Faults Log 20includes a number of records, where each record includes a system or OSEvent or Fault (column 24) and a time stamp (column 22) when the eventoccurred. When the management node detects a stability change in one ofthe servers 50, the trouble-shooting logic 12 can used the Log 20 forthat server to identify one or more software applications that wereinstalled on that server is the period prior to the stability change.

The Server Configuration data 30 includes a Server Identification(Server ID; column 32) that specifies one of the servers 50, a list ofhardware in each server (column 34), and a list of the softwareapplications installed on each server and the capabilities of eachsoftware application (column 36). The Server Configuration data 30 maybe obtained from the service processor 52 in each server 50. Morespecifically, each server 50 may include hardware vital product data(Hardware VPD) 54 and a list of installed software applications 56 thatare accessible to the service processor 52. Through communication witheach server 50, the management node 10 can obtain the necessary data topopulate and store the Server Configuration data 30.

The Problem/Solution Software List 40 is prepared by thetrouble-shooting logic 12 and may be shared with other computer systems,such as the management node 10′ and servers 50′, in accordance withembodiments of the present invention. Such a list may be shared, forexample, over an internal network, such as a local area network (LAN),or an external network, such as the Internet. The Problem/SolutionSoftware List 40 may, for example, include a plurality of records thatidentify software applications that have greater than a predeterminedlikelihood of responsibility for a stability change (column 42),identify the likelihood of responsibility associated with the softwareapplication (column 44), and an indication whether the stability changewas an increase in stability (+) or an increase in instability (−)(column 46).

FIG. 2 is a flowchart of a method 70 of identifying softwareapplications that have a likelihood of responsibility for systemstability changes in one or more of the servers or other computersystems of entities, including a virtual machine. Step 72 detects astability change in a computer system. Step 74 identifies a first set ofat least one capability of the computer system that is affected by thestability change. In response to detecting the stability change, Step 76identifies a software application that was installed or updated to thecomputer system prior to the stability change. A second set of at leastone capability of the computer system that is utilized by the identifiedsoftware application is identified in Step 78. Then, in Step 80, thefirst set of at least one capability is compared to the second set of atleast one capability to determine a degree of similarity. In Step 82, afirst time that the stability change was detected is compared to asecond time that the identified software application was installed orupdated to determine a temporal proximity. The likelihood that theidentified software application is the cause of the stability change isidentified in Step 84, wherein the identified likelihood is a functionof the degree of similarity and the temporal proximity.

It should be understood that although this disclosure is applicable tocloud computing, implementations of the teachings recited herein are notlimited to a cloud computing environment. Rather, embodiments of thepresent invention are capable of being implemented in conjunction withany other type of computing environment now known or later developed.

Cloud computing is a model of service delivery for enabling convenient,on-demand network access to a shared pool of configurable computingresources (e.g. networks, network bandwidth, servers, processing,memory, storage, applications, virtual machines, and services) that canbe rapidly provisioned and released with minimal management effort orinteraction with a provider of the service. This cloud model may includeat least five characteristics, at least three service models, and atleast four deployment models.

Characteristics are as Follows:

On-demand self-service: a cloud consumer can unilaterally provisioncomputing capabilities, such as server time and network storage, asneeded automatically without requiring human interaction with theservice's provider.

Broad network access: capabilities are available over a network andaccessed through standard mechanisms that promote use by heterogeneousthin or thick client platforms (e.g., mobile phones, laptops, and PDAs).

Resource pooling: the provider's computing resources are pooled to servemultiple consumers using a multi-tenant model, with different physicaland virtual resources dynamically assigned and reassigned according todemand. There is a sense of location independence in that the consumergenerally has no control or knowledge over the exact location of theprovided resources but may be able to specify location at a higher levelof abstraction (e.g., country, state, or datacenter).

Rapid elasticity: capabilities can be rapidly and elasticallyprovisioned, in some cases automatically, to quickly scale out andrapidly released to quickly scale in. To the consumer, the capabilitiesavailable for provisioning often appear to be unlimited and can bepurchased in any quantity at any time.

Measured service: cloud systems automatically control and optimizeresource use by leveraging a metering capability at some level ofabstraction appropriate to the type of service (e.g., storage,processing, bandwidth, and active user accounts). Resource usage can bemonitored, controlled, and reported providing transparency for both theprovider and consumer of the utilized service.

Service Models are as follows:

Software as a Service (SaaS): the capability provided to the consumer isto use the provider's applications running on a cloud infrastructure.The applications are accessible from various client devices through athin client interface such as a web browser (e.g., web-based e-mail).The consumer does not manage or control the underlying cloudinfrastructure including network, servers, operating systems, storage,or even individual application capabilities, with the possible exceptionof limited user-specific application configuration settings.

Platform as a Service (PaaS): the capability provided to the consumer isto deploy onto the cloud infrastructure consumer-created or acquiredapplications created using programming languages and tools supported bythe provider. The consumer does not manage or control the underlyingcloud infrastructure including networks, servers, operating systems, orstorage, but has control over the deployed applications and possiblyapplication hosting environment configurations.

Infrastructure as a Service (IaaS): the capability provided to theconsumer is to provision processing, storage, networks, and otherfundamental computing resources where the consumer is able to deploy andrun arbitrary software, which can include operating systems andapplications. The consumer does not manage or control the underlyingcloud infrastructure but has control over operating systems, storage,deployed applications, and possibly limited control of select networkingcomponents (e.g., host firewalls).

Deployment Models are as follows:

Private cloud: the cloud infrastructure is operated solely for anorganization. It may be managed by the organization or a third party andmay exist on-premises or off-premises.

Community cloud: the cloud infrastructure is shared by severalorganizations and supports a specific community that has shared concerns(e.g., mission, security requirements, policy, and complianceconsiderations). It may be managed by the organizations or a third partyand may exist on-premises or off-premises.

Public cloud: the cloud infrastructure is made available to the generalpublic or a large industry group and is owned by an organization sellingcloud services.

Hybrid cloud: the cloud infrastructure is a composition of two or moreclouds (private, community, or public) that remain unique entities butare bound together by standardized or proprietary technology thatenables data and application portability (e.g., cloud bursting forload-balancing between clouds).

A cloud computing environment is service oriented with a focus onstatelessness, low coupling, modularity, and semantic interoperability.At the heart of cloud computing is an infrastructure comprising anetwork of interconnected nodes.

Referring now to FIG. 3, a schematic of an example of a cloud computingnode is shown. Cloud computing node 110 is only one example of asuitable cloud computing node and is not intended to suggest anylimitation as to the scope of use or functionality of embodiments of theinvention described herein. Regardless, cloud computing node 110 iscapable of being implemented and/or performing any of the functionalityset forth hereinabove.

In cloud computing node 110 there is a computer system/server 112, whichis operational with numerous other general purpose or special purposecomputing system environments or configurations. Examples of well-knowncomputing systems, environments, and/or configurations that may besuitable for use with computer system/server 112 include, but are notlimited to, personal computer systems, server computer systems, thinclients, thick clients, hand-held or laptop devices, multiprocessorsystems, microprocessor-based systems, set top boxes, programmableconsumer electronics, network PCs, minicomputer systems, mainframecomputer systems, and distributed cloud computing environments thatinclude any of the above systems or devices, and the like.

Computer system/server 112 may be described in the general context ofcomputer system-executable instructions, such as program modules, beingexecuted by a computer system. Generally, program modules may includeroutines, programs, objects, components, logic, data structures, and soon that perform particular tasks or implement particular abstract datatypes. Computer system/server 112 may be practiced in distributed cloudcomputing environments where tasks are performed by remote processingdevices that are linked through a communications network. In adistributed cloud computing environment, program modules may be locatedin both local and remote computer system storage media including memorystorage devices.

As shown in FIG. 3, computer system/server 112 in cloud computing node110 is shown in the form of a general-purpose computing device. Thecomponents of computer system/server 112 may include, but are notlimited to, one or more processors or processing units 116, a systemmemory 128, and a bus 118 that couples various system componentsincluding system memory 128 to processor 116.

Bus 118 represents one or more of any of several types of busstructures, including a memory bus or memory controller, a peripheralbus, an accelerated graphics port, and a processor or local bus usingany of a variety of bus architectures. By way of example, and notlimitation, such architectures include Industry Standard Architecture(ISA) bus, Micro Channel Architecture (MCA) bus, Enhanced ISA (EISA)bus, Video Electronics Standards Association (VESA) local bus, andPeripheral Component Interconnects (PCI) bus.

Computer system/server 112 typically includes a variety of computersystem readable media. Such media may be any available media that isaccessible by computer system/server 112, and it includes both volatileand non-volatile media, removable and non-removable media.

System memory 128 can include computer system readable media in the formof volatile memory, such as random access memory (RAM) 130 and/or cachememory 132. Computer system/server 112 may further include otherremovable/non-removable, volatile/non-volatile computer system storagemedia. By way of example only, storage system 134 can be provided forreading from and writing to a non-removable, non-volatile magnetic media(not shown and typically called a “hard drive”). Although not shown, amagnetic disk drive for reading from and writing to a removable,non-volatile magnetic disk (e.g., a “floppy disk”), and an optical diskdrive for reading from or writing to a removable, non-volatile opticaldisk such as a CD-ROM, DVD-ROM or other optical media can be provided.In such instances, each can be connected to bus 118 by one or more datamedia interfaces. As will be further depicted and described below,memory 128 may include at least one program product having a set (e.g.,at least one) of program modules that are configured to carry out thefunctions of embodiments of the invention.

Program/utility 140, having a set (at least one) of program modules 142,may be stored in memory 128 by way of example, and not limitation, aswell as an operating system, one or more application programs, otherprogram modules, and program data. Each of the operating system, one ormore application programs, other program modules, and program data orsome combination thereof, may include an implementation of a networkingenvironment. Program modules 142 generally carry out the functionsand/or methodologies of embodiments of the invention as describedherein.

Computer system/server 112 may also communicate with one or moreexternal devices 114 such as a keyboard, a pointing device, a display124, etc.; one or more devices that enable a user to interact withcomputer system/server 112; and/or any devices (e.g., network card,modem, etc.) that enable computer system/server 112 to communicate withone or more other computing devices. Such communication can occur viaInput/Output (I/O) interfaces 122. Still yet, computer system/server 112can communicate with one or more networks such as a local area network(LAN), a general wide area network (WAN), and/or a public network (e.g.,the Internet) via network adapter 120. As depicted, network adapter 120communicates with the other components of computer system/server 112 viabus 118. It should be understood that although not shown, other hardwareand/or software components could be used in conjunction with computersystem/server 112. Examples, include, but are not limited to: microcode,device drivers, redundant processing units, external disk drive arrays,RAID systems, tape drives, and data archival storage systems, etc.

Referring now to FIG. 4, an illustrative cloud computing environment 150is depicted. As shown, the cloud computing environment 150 comprises oneor more cloud computing nodes 110 with which local computing devicesused by cloud consumers, such as, for example, personal digitalassistant (PDA) or cellular telephone 154A, desktop computer 154B,laptop computer 154C, and/or automobile computer system 154N maycommunicate. Nodes 110 may communicate with one another. They may begrouped (not shown) physically or virtually, in one or more networks,such as Private, Community, Public, or Hybrid clouds as describedhereinabove, or a combination thereof. This allows cloud computingenvironment 150 to offer infrastructure, platforms and/or software asservices for which a cloud consumer does not need to maintain resourceson a local computing device. It is understood that the types ofcomputing devices 154A-N shown in FIG. 4 are intended to be illustrativeonly and that computing nodes 110 and cloud computing environment 150can communicate with any type of computerized device over any type ofnetwork and/or network addressable connection (e.g., using a webbrowser).

Referring now to FIG. 5, a set of functional abstraction layers providedby cloud computing environment 150 (Shown in FIG. 4) is shown. It shouldbe understood in advance that the components, layers, and functionsshown in FIG. 5 are intended to be illustrative only and embodiments ofthe invention are not limited thereto. As depicted, the following layersand corresponding functions are provided:

Hardware and software layer 160 includes hardware and softwarecomponents. Examples of hardware components include mainframes, in oneexample IBM® zSeries® systems; RISC (Reduced Instruction Set Computer)architecture based servers, in one example IBM pSeries® systems; IBMxSeries® systems; IBM BladeCenter® systems; storage devices; networksand networking components. Examples of software components includenetwork application server software, in one example IBM WebSphere®application server software; and database software, in one example IBMDB2® database software. (IBM, zSeries, pSeries, xSeries, BladeCenter,WebSphere, and DB2 are trademarks of International Business MachinesCorporation registered in many jurisdictions worldwide).

Virtualization layer 162 provides an abstraction layer from which thefollowing examples of virtual entities may be provided: virtual servers;virtual storage; virtual networks, including virtual private networks;virtual applications and operating systems; and virtual clients.

In one example, management layer 164 may provide the functions describedbelow. Resource provisioning provides dynamic procurement of computingresources and other resources that are utilized to perform tasks withinthe cloud computing environment. Metering and Pricing provide costtracking as resources are utilized within the cloud computingenvironment, and billing or invoicing for consumption of theseresources. In one example, these resources may comprise applicationsoftware licenses. Security provides identity verification for cloudconsumers and tasks, as well as protection for data and other resources.User portal provides access to the cloud computing environment forconsumers and system administrators. Service level management providescloud computing resource allocation and management such that requiredservice levels are met. Service Level Agreement (SLA) planning andfulfillment provides pre-arrangement for, and procurement of, cloudcomputing resources for which a future requirement is anticipated inaccordance with an SLA.

Workloads layer 166 provides examples of functionality for which thecloud computing environment may be utilized. Examples of workloads andfunctions which may be provided from this layer include: mapping andnavigation; software development and lifecycle management; virtualclassroom education delivery; data analytics processing; and transactionprocessing.

FIG. 6 depicts an exemplary computing node (or simply “computer”) 202that may be utilized in accordance with one or more embodiments of thepresent invention. Note that some or all of the exemplary architecture,including both depicted hardware and software, shown for and withincomputer 202 may be utilized by the software deploying server 250, aswell as the provisioning manager/management node 222 and the serverblades 304 a-n shown in FIG. 7. Note that while the server bladesdescribed in the present disclosure are described and depicted inexemplary manner as server blades in a blade chassis, some or all of thecomputers described herein may be stand-alone computers, servers, orother integrated or stand-alone computing devices. Thus, the terms“blade,” “server blade,” “computer,” and “server” are usedinterchangeably in the present descriptions.

Computer 202 includes a processor unit 204 that is coupled to a systembus 206. Processor unit 204 may utilize one or more processors, each ofwhich has one or more processor cores. A video adapter 208, whichdrives/supports a display 210, is also coupled to system bus 206. In oneembodiment, a switch 207 couples the video adapter 208 to the system bus206. Alternatively, the switch 207 may couple the video adapter 208 tothe display 210. In either embodiment, the switch 207 is a switch,preferably mechanical, that allows the display 210 to be coupled to thesystem bus 206, and thus to be functional only upon execution ofinstructions (e.g., virtual machine provisioning program—VMPP 248described below) that support the processes described herein.

System bus 206 is coupled via a bus bridge 212 to an input/output (I/O)bus 214. An I/O interface 216 is coupled to I/O bus 214. I/O interface216 affords communication with various I/O devices, including a keyboard218, a mouse 220, a media tray 222 (which may include storage devicessuch as CD-ROM drives, multi-media interfaces, etc.), a printer 224, and(if a VHDL chip 237 is not utilized in a manner described below),external USB port(s) 226. While the format of the ports connected to I/Ointerface 216 may be any known to those skilled in the art of computerarchitecture, in a preferred embodiment some or all of these ports areuniversal serial bus (USB) ports.

As depicted, computer 202 is able to communicate with a softwaredeploying server 250 via network 228 using a network interface 230.Network 228 may be an external network such as the Internet, or aninternal network such as an Ethernet or a virtual private network (VPN).

A hard drive interface 232 is also coupled to system bus 206. Hard driveinterface 232 interfaces with a hard drive 234. In a preferredembodiment, hard drive 234 populates a system memory 236, which is alsocoupled to system bus 206. System memory is defined as a lowest level ofvolatile memory in computer 202. This volatile memory includesadditional higher levels of volatile memory (not shown), including, butnot limited to, cache memory, registers and buffers. Data that populatessystem memory 236 includes computer 202's operating system (OS) 238 andapplication programs 244.

The operating system 238 includes a shell 240, for providing transparentuser access to resources such as application programs 244. Generally,shell 240 is a program that provides an interpreter and an interfacebetween the user and the operating system. More specifically, shell 240executes commands that are entered into a command line user interface orfrom a file. Thus, shell 240, also called a command processor, isgenerally the highest level of the operating system software hierarchyand serves as a command interpreter. The shell provides a system prompt,interprets commands entered by keyboard, mouse, or other user inputmedia, and sends the interpreted command(s) to the appropriate lowerlevels of the operating system (e.g., a kernel 242) for processing. Notethat while shell 240 is a text-based, line-oriented user interface, thepresent invention will equally well support other user interface modes,such as graphical, voice, gestural, etc.

As depicted, OS 238 also includes kernel 242, which includes lowerlevels of functionality for OS 238, including providing essentialservices required by other parts of OS 238 and application programs 244,including memory management, process and task management, diskmanagement, and mouse and keyboard management.

Application programs 244 include a renderer, shown in exemplary manneras a browser 246. Browser 246 includes program modules and instructionsenabling a world wide web (WWW) client (i.e., computer 202) to send andreceive network messages to the Internet using hypertext transferprotocol (HTTP) messaging, thus enabling communication with softwaredeploying server 250 and other described computer systems.

Application programs 244 in the system memory of computer 202 (as wellas the system memory of the software deploying server 250) also includea virtual machine provisioning program (VMPP) 248. VMPP 248 is able tocommunicate with a vital product data (VPD) table 251, which providesrequired VPD data described below. In one embodiment, the computer 202is able to download VMPP 248 from software deploying server 250,including in an on-demand basis.

Also stored in the system memory 236 is a VHDL (VHSIC hardwaredescription language) program 239. VHDL is an exemplary design-entrylanguage for field programmable gate arrays (FPGAs), applicationspecific integrated circuits (ASICs), and other similar electronicdevices. In one embodiment, execution of instructions from VMPP 248causes the VHDL program 239 to configure the VHDL chip 237, which may bean FPGA, ASIC, or the like.

In another embodiment of the present invention, execution ofinstructions from VMPP 248 results in a utilization of VHDL program 239to program a VHDL emulation chip 251. VHDL emulation chip 251 mayincorporate a similar architecture as described above for VHDL chip 237.Once VMPP 248 and VHDL program 239 program VHDL emulation chip 251, VHDLemulation chip 251 performs, as hardware, some or all functionsdescribed by one or more executions of some or all of the instructionsfound in VMPP 248. That is, the VHDL emulation chip 251 is a hardwareemulation of some or all of the software instructions found in VMPP 248.In one embodiment, VHDL emulation chip 251 is a programmable read onlymemory (PROM) that, once burned in accordance with instructions fromVMPP 248 and VHDL program 239, is permanently transformed into a newcircuitry that performs the functions needed to perform the processes ofthe present invention.

The hardware elements depicted in computer 202 are not intended to beexhaustive, but rather are representative to highlight essentialcomponents required by the present invention. For instance, computer 202may include alternate memory storage devices such as magnetic cassettes,digital versatile disks (DVDs), Bernoulli cartridges, and the like.These and other variations are intended to be within the spirit andscope of the present invention.

A cloud computing environment allows a user workload to be assigned avirtual machine (VM) somewhere in the computing cloud. This virtualmachine provides the software operating system and physical resourcessuch as processing power and memory to support the user's applicationworkload. The present disclosure describes methods for dynamicallymigrating virtual machine among physical servers based on the cachedemand of the virtual machine workload. As described above, one of thosemethods comprises obtaining a cache hit ratio for each of a plurality ofvirtual machines; identifying, from among the plurality of virtualmachines, a first virtual machine having a cache hit ratio that is lessthan a threshold ratio, wherein the first virtual machine is running ona first physical server; and migrating the first virtual machine fromthe first physical server having a first cache size to a second physicalserver having a second cache size that is greater than the first cachesize.

FIG. 7 depicts an exemplary blade chassis that may be utilized inaccordance with one or more embodiments of the present invention. Theexemplary blade chassis 302 may operate in a “cloud” environment toprovide a pool of resources. Blade chassis 302 comprises a plurality ofblades 304 a-n (where “a-n” indicates an integer number of blades)coupled to a chassis backbone 306. Each blade supports one or morevirtual machines (VMs). As known to those skilled in the art ofcomputers, a VM is a software implementation (emulation) of a physicalcomputer. A single hardware computer (blade) can support multiple VMs,each running the same, different, or shared operating systems. In oneembodiment, each VM can be specifically tailored and reserved forexecuting software tasks 1) of a particular type (e.g., databasemanagement, graphics, word processing etc.); 2) for a particular user,subscriber, client, group or other entity; 3) at a particular time ofday or day of week (e.g., at a permitted time of day or schedule); etc.

As depicted in FIG. 7, blade 304 a supports VMs 308 a-n (where “a-n”indicates an integer number of VMs), and blade 304 n supports VMs 310a-n (wherein “a-n” indicates an integer number of VMs). The blades 304a-n are coupled to a storage device 312 that provides a hypervisor 314,guest operating systems, and applications for users (not shown).Provisioning software from the storage device 312 allocates boot storagewithin the storage device 312 to contain the maximum number of guestoperating systems, and associates applications based on the total amountof storage (such as that found within storage device 312) within thecloud. For example, support of one guest operating system and itsassociated applications may require 1 GByte of physical memory storagewithin storage device 312 to store the application, and another 1 GByteof memory space within storage device 312 to execute that application.If the total amount of memory storage within a physical server, such asboot storage device 312, is 64 GB, the provisioning software assumesthat the physical server can support 32 virtual machines. Thisapplication can be located remotely in the network 316 and transmittedfrom the network attached storage 317 to the storage device 312 over thenetwork. The global provisioning manager 332 running on the remotemanagement node (Director Server) 330 performs this task. In thisembodiment, the computer hardware characteristics are communicated fromthe VPD 251 to the VMPP 248. The VMPP 248 communicates the computerphysical characteristics to the blade chassis provisioning manager 322,to the management interface 320, and to the global provisioning manager332 running on the remote management node (Director Server) 330.

Note that chassis backbone 306 is also coupled to a network 316, whichmay be a public network (e.g., the Internet), a private network (e.g., avirtual private network or an actual internal hardware network), etc.Network 316 permits a virtual machine workload 318 to be communicated toa management interface 320 of the blade chassis 302. This virtualmachine workload 318 is a software task whose execution, on any of theVMs within the blade chassis 302, is to request and coordinatedeployment of workload resources with the management interface 320. Themanagement interface 320 then transmits this workload request to aprovisioning manager/management node 322, which is hardware and/orsoftware logic capable of configuring VMs within the blade chassis 302to execute the requested software task. In essence the virtual machineworkload 318 manages the overall provisioning of VMs by communicatingwith the blade chassis management interface 320 and provisioningmanagement node 322. Then this request is further communicated to theVMPP 148 in the computer system. Note that the blade chassis 302 is anexemplary computer environment in which the presently disclosed methodscan operate. The scope of the presently disclosed system should not belimited to a blade chassis, however. That is, the presently disclosedmethods can also be used in any computer environment that utilizes sometype of workload management or resource provisioning, as describedherein. Thus, the terms “blade chassis,” “computer chassis,” and“computer environment” are used interchangeably to describe a computersystem that manages multiple computers/blades/servers.

As will be appreciated by one skilled in the art, aspects of the presentinvention may be embodied as a system, method or computer programproduct. Accordingly, aspects of the present invention may take the formof an entirely hardware embodiment, an entirely software embodiment(including firmware, resident software, micro-code, etc.) or anembodiment combining software and hardware aspects that may allgenerally be referred to herein as a “circuit,” “module” or “system.”Furthermore, aspects of the present invention may take the form of acomputer program product embodied in one or more computer readablemedium(s) having computer readable program code embodied thereon.

Any combination of one or more computer readable medium(s) may beutilized. The computer readable medium may be a computer readable signalmedium or a computer readable storage medium. A computer readablestorage medium may be, for example, but not limited to, an electronic,magnetic, optical, electromagnetic, infrared, or semiconductor system,apparatus, or device, or any suitable combination of the foregoing. Morespecific examples (a non-exhaustive list) of the computer readablestorage medium would include the following: an electrical connectionhaving one or more wires, a portable computer diskette, a hard disk, arandom access memory (RAM), a read-only memory (ROM), an erasableprogrammable read-only memory (EPROM or Flash memory), an optical fiber,a portable compact disc read-only memory (CD-ROM), an optical storagedevice, a magnetic storage device, or any suitable combination of theforegoing. In the context of this document, a computer readable storagemedium may be any tangible medium that can contain, or store a programfor use by or in connection with an instruction execution system,apparatus, or device.

A computer readable signal medium may include a propagated data signalwith computer readable program code embodied therein, for example, inbaseband or as part of a carrier wave. Such a propagated signal may takeany of a variety of forms, including, but not limited to,electro-magnetic, optical, or any suitable combination thereof. Acomputer readable signal medium may be any computer readable medium thatis not a computer readable storage medium and that can communicate,propagate, or transport a program for use by or in connection with aninstruction execution system, apparatus, or device.

Program code embodied on a computer readable medium may be transmittedusing any appropriate medium, including but not limited to wireless,wireline, optical fiber cable, RF, etc., or any suitable combination ofthe foregoing.

Computer program code for carrying out operations for aspects of thepresent invention may be written in any combination of one or moreprogramming languages, including an object oriented programming languagesuch as Java, Smalltalk, C++ or the like and conventional proceduralprogramming languages, such as the “C” programming language or similarprogramming languages. The program code may execute entirely on theuser's computer, partly on the user's computer, as a stand-alonesoftware package, partly on the user's computer and partly on a remotecomputer or entirely on the remote computer or server. In the latterscenario, the remote computer may be connected to the user's computerthrough any type of network, including a local area network (LAN) or awide area network (WAN), or the connection may be made to an externalcomputer (for example, through the Internet using an Internet ServiceProvider).

Aspects of the present invention are described below with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems) and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer program instructions. These computer program instructions maybe provided to a processor of a general purpose computer, specialpurpose computer, or other programmable data processing apparatus toproduce a machine, such that the instructions, which execute via theprocessor of the computer or other programmable data processingapparatus, create means for implementing the functions/acts specified inthe flowchart and/or block diagram block or blocks.

These computer program instructions may also be stored in a computerreadable medium that can direct a computer, other programmable dataprocessing apparatus, or other devices to function in a particularmanner, such that the instructions stored in the computer readablemedium produce an article of manufacture including instructions whichimplement the function/act specified in the flowchart and/or blockdiagram block or blocks.

The computer program instructions may also be loaded onto a computer,other programmable data processing apparatus, or other devices to causea series of operational steps to be performed on the computer, otherprogrammable apparatus or other devices to produce a computerimplemented process such that the instructions which execute on thecomputer or other programmable apparatus provide processes forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks.

The flowchart and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods and computer program products according to variousembodiments of the present invention. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof code, which comprises one or more executable instructions forimplementing the specified logical function(s). It should also be notedthat, in some alternative implementations, the functions noted in theblock may occur out of the order noted in the figures. For example, twoblocks shown in succession may, in fact, be executed substantiallyconcurrently, or the blocks may sometimes be executed in the reverseorder, depending upon the functionality involved. It will also be notedthat each block of the block diagrams and/or flowchart illustration, andcombinations of blocks in the block diagrams and/or flowchartillustration, can be implemented by special purpose hardware-basedsystems that perform the specified functions or acts, or combinations ofspecial purpose hardware and computer instructions.

The terminology used herein is for the purpose of describing particularembodiments only and is not intended to be limiting of the invention. Asused herein, the singular forms “a”, “an” and “the” are intended toinclude the plural forms as well, unless the context clearly indicatesotherwise. It will be further understood that the terms “comprises”and/or “comprising,” when used in this specification, specify thepresence of stated features, integers, steps, operations, elements,components and/or groups, but do not preclude the presence or additionof one or more other features, integers, steps, operations, elements,components, and/or groups thereof. The terms “preferably,” “preferred,”“prefer,” “optionally,” “may,” and similar terms are used to indicatethat an item, condition or step being referred to is an optional (notrequired) feature of the invention.

The corresponding structures, materials, acts, and equivalents of allmeans or steps plus function elements in the claims below are intendedto include any structure, material, or act for performing the functionin combination with other claimed elements as specifically claimed. Thedescription of the present invention has been presented for purposes ofillustration and description, but it is not intended to be exhaustive orlimited to the invention in the form disclosed. Many modifications andvariations will be apparent to those of ordinary skill in the artwithout departing from the scope and spirit of the invention. Theembodiment was chosen and described in order to best explain theprinciples of the invention and the practical application, and to enableothers of ordinary skill in the art to understand the invention forvarious embodiments with various modifications as are suited to theparticular use contemplated.

What is claimed is:
 1. A computer-implemented method, comprising:detecting a stability change in a computer system; identifying a firstset of at least one capability of the computer system that is affectedby the stability change; identifying, in response to detecting thestability change, a software application that was installed or updatedto the computer system prior to the stability change; identifying asecond set of at least one capability of the computer system that isutilized by the identified software application; comparing the first setof at least one capability to the second set of at least one capabilityto determine a degree of similarity; comparing a first time that thestability change was detected to a second time that the identifiedsoftware application was installed or updated to determine a temporalproximity; and identifying the likelihood that the identified softwareapplication is the cause of the stability change, wherein the identifiedlikelihood is a function of the degree of similarity and the temporalproximity.
 2. The computer-implemented method of claim 1, wherein thecomputer system includes a management node and a plurality of servers incommunication with the management node.
 3. The computer-implementedmethod of claim 1, wherein the first set of at least one capability andthe second set of at least one capability include one or more capabilityindependently selected from CPU utilization, memory utilization, andnetwork connectivity.
 4. The computer-implemented method of claim 1,wherein the identified software application is an update to a driver orfirmware.
 5. The computer-implemented method of claim 1, wherein theidentified software application is an updated version of a previouslyinstalled software application.
 6. The computer-implemented method ofclaim 1, wherein the identified software application includes a driverfor a hard disk drive, a network interface, or an input/output port. 7.The computer-implemented method of claim 1, further comprising:informing other computer systems that the identified softwareapplication may cause a stability change.
 8. The computer-implementedmethod of claim 1, further comprising: preparing a list of softwareapplications including the name of the identified software applicationand the likelihood that the identified software application is the causeof the stability change.
 9. The computer-implemented method of claim 8,wherein the list of software applications includes software applicationslikely to increase stability and software applications likely toincrease instability.
 10. The computer-implemented method of claim 1,wherein the stability change is an increase in an amount of stability.11. The computer-implemented method of claim 1, wherein the stabilitychange is an increase in an amount of instability.
 12. Thecomputer-implemented method of claim 11, further comprising: thecomputer system removing the identified software application.
 13. Thecomputer-implemented method of claim 11, further comprising: thecomputer system installing an updated version of the identified softwareapplication.
 14. The computer-implemented method of claim 11, whereinthe step of detecting a stability change in a computer system includesdetecting that CPU utilization is greater than a predetermined CPUutilization threshold, detecting that network utilization is less than apredetermined network utilization threshold, or detecting that memoryutilization is less than a predetermined memory utilization threshold.15. The computer-implemented method of claim 1, further comprising:informing at least one other computer system of the likelihood that theidentified software application is the cause of the stability change.16. The computer-implemented method of claim 1, further comprisingpreparing a list of software applications having greater than apredetermined likelihood as being the cause of instability in thecomputer system, and providing the list to at least one other computersystem.
 17. The computer-implemented method of claim 16, furthercomprising: the other computer system, in response to receiving thelist, avoiding installation of any of the software applications on thelist.
 18. The computer-implemented method of claim 1, further comprisingpreparing a list of software applications having greater than apredetermined likelihood as being the cause of stability in the computersystem, and providing the list to at least one other computer system.19. The computer-implemented method of claim 18, further comprising: theother computer system, in response to receiving the list, installing oneor more of the software applications on the list.
 20. Thecomputer-implemented method of claim 19, wherein the other computersystem installs one of the software applications on the list that is anupdate of a software application already installed on the other computersystem.